In this paper we explore the dynamics of this system using a Gaussian threshold distribution. It is not necessary to truncate the distribution, since we can simply assume that if the threshold is \({<}0\)  (or \({>}1\) ), an individual will always be updated to its preferred state independent of its neighborhood configuration. We expect other flexible distributions to give similar qualitative results. For example, even uniform distributions show the same basic bifurcations that we explore here [1]}. We have also tried simulations with bimodal superpositions of Gaussians, and again seen qualitatively similar results.
